背景:我们的目的是开发和评估一种在12通道心电图(ECG)期间测量肌肉质量的方法,确定过度水合患者肌肉减少症的发生率并纠正其充血。
方法:同时提供多频分段阻抗数据的12通道ECG用于测量全身水分(TBW),细胞外水(ECW),ECW/TBW比率和阑尾肌肉质量(AppMM),通过全身双能X射线吸收法验证。年轻(年龄范围20-25岁)健康男性(n=77)和女性(n=88)的平均ECW/TBW比为0.24±0.018(SD)和0.25±0.016,分别。在869名健康对照和765名纽约心脏病协会II-IV级慢性心力衰竭(CHF)患者中,ECW/TBW比率与该平均值的偏差用于校正AppMM的过量ECW(\'干AppMM\')。还在443名对照和患者中检查了AppMM和干AppMM与握力的关联。
结果:随着N末端脑钠肽前体(NT-proBNP)的增加,观察到AppMM指数的持续下降,对于干AppMM指数更为明显(对于NT-proBNP<125pg/mL的男性:AppMM指数平均值=8.4±1.05,AppMM指数干平均值=8.0±1.46[n=201,P<0.001];对于NT-proBNP<150pg/mL的女性:AppMM指数平均值=6.4±1.0,AppMM指数干平均值=5.8±1.18[n=198,P<0.001];对于AppmeanNT-prAppMM与上身AppMM和握力(r值)的相关性从0.79增加到0.83(P<0.001),从0.80增加到0.84(P<0.001)。分别,校正后(n=443)。在ECW修正后,AppMM随年龄的下降比预期的要陡峭得多,尤其是男性:在CHF和少肌症患者中,根据欧洲人的说法,纠正ECW过量后,肌肉减少症的发病率可能会高出30%(62%vs.57%,对于男性来说,和43%vs.31%,女性)和美国国立卫生研究院基金会(FNIH)(56%vs.46%,对于男性来说,和54%vs.38%,对于女性)共识准则。
结论:根据欧洲肌肉减少症工作组和FNIH共识定义,在校正ECW过量后,CHF中肌肉减少症的发生率可能会高出30%。这种校正改善了肌肉质量和力量之间的相关性。提出的技术将有助于,大规模地,筛查肌肉减少症,帮助识别机制并提高对临床结果的理解。
BACKGROUND: Our aim was to develop and evaluate a method for the measurement of muscle mass during the 12-channel electrocardiogram (ECG), to determine the incidence of sarcopenia in patients with overhydration and to correct it for congestion.
METHODS: A 12-channel ECG that simultaneously provided multifrequency segmental impedance data was used to measure total body water (TBW), extracellular water (ECW), ECW/TBW ratio and appendicular muscle mass (AppMM), validated by whole-body dual-energy X-ray absorptiometry. The mean ECW/TBW ratio was 0.24 ± 0.018 (SD) and 0.25 ± 0.016 for young (age range 20-25 years) healthy males (n = 77) and females (n = 88), respectively. The deviation of the ECW/TBW ratio from this mean was used to correct AppMM for excess ECW (\'dry AppMM\') in 869 healthy controls and in 765 patients with chronic heart failure (CHF) New York Heart Association classes II-IV. The association of AppMM and dry AppMM with grip strength was also examined in 443 controls and patients.
RESULTS: With increasing N-terminal pro-brain natriuretic peptide (NT-proBNP), a continuous decline of AppMM indices is observed, which is more pronounced for dry AppMM indices (for males with NT-proBNP < 125 pg/mL: AppMM index mean = 8.4 ± 1.05, AppMM index dry mean = 8.0 ± 1.46 [n = 201, P < 0.001]; for females with NT-proBNP < 150 pg/mL: AppMM index mean = 6.4 ± 1.0, AppMM index dry mean = 5.8 ± 1.18 [n = 198, P < 0.001]; for males with NT-proBNP > 1000 pg/mL: AppMM index mean = 7.6 ± 0.98, AppMM index dry mean = 6.2 ± 1.11 [n = 137, P < 0.001]; and for females with NT-proBNP > 1000 pg/mL: AppMM index mean = 5.9 ± 0.96, AppMM index dry mean = 4.8 ± 0.94 [n = 109, P < 0.001]). The correlation between AppMM and upper-body AppMM and grip strength (r-value) increased from 0.79 to 0.83 (P < 0.001) and from 0.80 to 0.84 (P < 0.001), respectively, after correction (n = 443). The decline of AppMM with age after correction for ECW is much steeper than appreciated, especially in males: In patients with CHF and sarcopenia, the incidence of sarcopenia may be up to 30% higher after correction for ECW excess according to the European (62% vs. 57%, for males, and 43% vs. 31%, for females) and Foundation for the National Institutes of Health (FNIH) (56% vs. 46%, for males, and 54% vs. 38%, for females) consensus guidelines.
CONCLUSIONS: The incidence of sarcopenia in CHF as defined by the European Working Group on Sarcopenia and FNIH consensus may be up to 30% higher after correction for ECW excess. This correction improves the correlation between muscle mass and strength. The presented technology will facilitate, on a large scale, screening for sarcopenia, help identify mechanisms and improve understanding of clinical outcomes.